Neural Correlates of Anesthesia in Newborn Mice and Humans

Monitoring the hypnotic component of anesthesia during surgeries is critical to prevent intraoperative awareness and reduce adverse side effects. For this purpose, electroencephalographic (EEG) methods complementing measures of autonomic functions and behavioral responses are in use in clinical prac...

Full description

Saved in:
Bibliographic Details
Published inFrontiers in neural circuits Vol. 13; p. 38
Main Authors Chini, Mattia, Gretenkord, Sabine, Kostka, Johanna K, Pöpplau, Jastyn A, Cornelissen, Laura, Berde, Charles B, Hanganu-Opatz, Ileana L, Bitzenhofer, Sebastian H
Format Journal Article
LanguageEnglish
Published Switzerland Frontiers Research Foundation 22.05.2019
Frontiers Media S.A
Subjects
Age
Algorithms
Anesthesia
Anesthesiology
Anesthetics
Anesthetics - pharmacology
Animals
Animals, Newborn
Brain - drug effects
Brain - physiology
Consciousness
development
EEG
Electroencephalography
Female
human
Humans
Infant
Infant, Newborn
Infants
Laboratory animals
Learning algorithms
LFP
Machine Learning
Male
Mice
Mice, Inbred C57BL
mouse
Neonates
Neuroscience
United States > US
mouse
development
EEG
LFP
machine learning
network dynamics
human
anesthesia
Online AccessGet full text

Cover

More Information
Summary:Monitoring the hypnotic component of anesthesia during surgeries is critical to prevent intraoperative awareness and reduce adverse side effects. For this purpose, electroencephalographic (EEG) methods complementing measures of autonomic functions and behavioral responses are in use in clinical practice. However, in human neonates and infants existing methods may be unreliable and the correlation between brain activity and anesthetic depth is still poorly understood. Here, we characterized the effects of different anesthetics on brain activity in neonatal mice and developed machine learning approaches to identify electrophysiological features predicting inspired or end-tidal anesthetic concentration as a proxy for anesthetic depth. We show that similar features from EEG recordings can be applied to predict anesthetic concentration in neonatal mice and humans. These results might support a novel strategy to monitor anesthetic depth in human newborns.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Edited by: Tommaso Pizzorusso, University of Florence, Italy
These authors have contributed equally to this work
Reviewed by: Paola Binda, University of Pisa, Italy; Laura Baroncelli, Italian National Research Council (CNR), Italy
Present address: Sebastian H. Bitzenhofer, Center for Neural Circuits and Behavior, Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
ISSN:1662-5110
1662-5110
DOI:10.3389/fncir.2019.00038